Competing risks analysis for discrete time‐to‐event data. (8th September 2020)

• Record Type: Journal Article
• Authors: Schmid, Matthias; Berger, Moritz
• Is Part Of: Wiley interdisciplinary reviews. Volume 13:Number 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-08
• Subjects: cause‐specific hazards model -- competing events -- cumulative incidence function -- discrete time‐to‐event analysis -- subdistribution hazard model; Mathematical statistics -- Data processing -- Periodicals; Science -- Data processing -- Periodicals; Social sciences -- Data processing -- Periodicals; Mathematical statistics -- Periodicals; 519.50285
• DOI: 10.1002/wics.1529
• Languages: English
• ISSNs: 1939-5108

Abstract

Abstract: This article presents an overview of statistical methods for the analysis of discrete failure times with competing events. We describe the most commonly used modeling approaches for this type of data, including discrete versions of the cause‐specific hazards model and the subdistribution hazard model. In addition to discussing the characteristics of these methods, we present approaches to nonparametric estimation and model validation. Our literature review suggests that discrete competing‐risks analysis has gained substantial interest in the research community and is used regularly in econometrics, biostatistics, and educational research. This article is categorized under: Statistical Models > Survival Models Statistical Models > Semiparametric Models Statistical Models > Generalized Linear Models Abstract : Illustration of tree‐based analysis of discrete‐time competing‐risks data.